This invention relates to programmable logic controllers (PLCs) and manufacturing process managers (MPMs) and, more particularly, to a data collection method for an MPM coupled to monitor a plurality of data points in each of a plurality of PLCs.
Programmable logic controllers (PLCs) are a relatively recent development in process control technology. As a part of process control, a programmable logic controller is used to monitor input signals from a variety of input points (input sensors) which report events and conditions occurring in a controlled process. For example, a PLC can monitor such input conditions as motor speed, temperature, pressure, volumetric flow, and the like. A control program is stored in a memory within the PLC to instruct the PLC what actions to take upon encountering particular input signals or conditions. In response to these input signals provided by input sensors, the PLC derives and generates output signals which are transmitted via PLC output points to various output devices to control a process. For example, the PLC may issue output signals to speed up or slow down a conveyer, rotate the arm of a robot, open or close a relay, raise or lower temperature as well as many other possible control functions too numerous to list.
Manufacturing process managers (MPMs) are dedicated host processors or computers used in manufacturing process control. In an exemplary distributed factory control system, PLCs are coupled to manage specific machines. Various machines may be grouped to form work cells with each machine in a cell being under the control of a separate corresponding PLC. (While one PLC could control multiple machines, in factories using assembly line techniques, it is desirable for maintenance purposes to have a one-to-one relationship between PLCs and machines.) Each work cell is assigned to a corresponding MPM which is responsible for monitoring, controlling, and coordinating the manufacturing devices and resources within a work cell and integrating the work cell with the rest of the factory. Thus, each MPM monitors a plurality of PLCs.
In the past, it has proven to be difficult for MPMs to collect data from a very large number of input points in a very short amount of time. However, on a shop floor where automated manufacturing is being conducted, exactly this situation is encountered. To illustrate the problem, an example is postulated wherein a manufacturing work cell includes 3500 points spread over a plurality of PLCs for which data collection is desired. One straightforward method of data collection is for the MPMs associated with the work cell to scan or poll all 3500 points all of the time. More specifically, each time the MPM scans a point, the current value of the point stored in a PLC is compared with the old value for that point. If a change between the present value and the old value is detected, an alarm message is generated and is appropriately annunciated to the user by the MPM system.
The above described approach is perfectly satisfactory as long as time is not of the essence. However, in actual practice, the time between the occurrence of the condition causing the alarm and the actual annunciation of the alarm may be unsatisfactorily long. Moreover, the number of messages which must be transmitted to request the input point information is very high in the above approach. More specifically, in a system where the maximum number of input points which can be requested by a particular message is 30, for example, it would require 117 messages to scan all 3500 input points. The transmission of such a high number of messages and the collection of data by the scanning method described above requires an unsatisfactorily large amount of time when time is of the essence.